What is Capacity Management in ITIL?

Capacity management is the practice of right-sizing IT resources to meet current and future needs. It’s also one of five areas of ITIL Service Delivery.

Effective capacity management is proactive, not reactive. Those doing well at capacity management make sure that business and service needs are met with a minimum of IT resources.

What's Included in Capacity Management in ITIL?

There are many IT tasks that fall under the umbrella of a capacity management process. Here are some of them:

◉ Monitor, analyze, and optimize IT resource utilization

◉ Manage demand for computing resources (this requires an understanding of business priorities)

◉ Create a model of infrastructure performance to understand future resource needs

◉ Right-size applications to make sure service levels can be met (without overdoing it)

◉ Produce a capacity plan that covers current use, forecasted needs, and support costs for new applications/releases

◉ Build the annual infrastructure growth plan with input from other teams

5 Steps to Successful Capacity Management

As with all major projects, proper planning is key. If you’re looking to get your project off the ground, here are the five steps you should take. To plan for where your capacity is going, you need to know where you’re at. That’s why it’s important to identify a capacity manager and form a capacity management team.

This team can then:

◉ Develop a mission, including desired end-state goals, processes, and responsibilities
◉ Assess the current state of capacity management
◉ Evaluate existing capacity management skills of the IT staff
◉ Take inventory of tools and software currently used for monitoring, capacity planning, performance management, and chargeback
◉ Collect budget details for capacity management work
◉ Perform a gap analysis to reveal areas that require process improvements, training, or software

Why Should I Implement Capacity Management?

Capacity management is critical to keeping IT costs down and quality of service up.

Most organizations use it to:

◉ Get more out of existing IT resources
◉ Improve IT cost per service unit positions
◉ Fine-tune applications and infrastructure components
◉ Improve performance, reduce consumption, and delay upgrades
◉ Eliminate redundant work
◉ Ensure consistent reporting
◉ Provision capacity efficiently
◉ Make informed business decisions using timely capacity and related cost information
◉ Provide insight into the total cost of ownership (TCO) of IT upgrades and initiatives
◉ Predict future use based on growth levels
◉ Uncover bottlenecks with enough time to stop them before service is affected

Capacity management teams also have close ties to ITIL service level management and financial management areas.

In fact, capacity management processes lead to a more thorough service level and associated financial information for the business. And this helps business leaders make more informed decisions.

Where Do I Start?

Capacity management is often the starting point for an ITIL Service Delivery initiative.

Here’s why. It offers quick, early wins. And these typically create enough cost savings to fund the remainder of your ITIL project. In our experience, such savings are typically in the millions of dollars.

Plus, recovering implementation costs and showing success keeps the project afloat. (This also encourages upper management to stay the course and reduces resistance in your organization.)

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DOE: The Power Tool of the Analyze and Improve Phases

Even a novice on a Six Sigma project team knows each step in the basic five-step DMAIC method (Define, Measure, Analyze, Improve, Control) is essential to the success of a breakthrough project. What is not as widely recognized, however, is that each step brings a distinct set of tools to bear on the project objective. For the Analyze and Improve steps, design of experiments (DOE), combined with analysis of variance, is the Six Sigma power tool.

Design of experiments was first conceived and developed by Sir Ronald A. Fisher in the 1920s and 1930s. Fisher was a brilliant mathematician and geneticist working to improve crop yields in England. He designed and supervised field trials comparing fertilizers and seed varieties, among other things. Fisher encountered two enormous obstacles: 1) uncontrollable variation in the soil from plot to plot and 2) a limited number of plots available for any given trial. He solved these problems by the arrangement of the fertilizers or seed varieties in the field.

For example, to determine which of four varieties of wheat had the highest yield, Fisher would divide a rectangular test field into 16 plots. He then planted each of the four varieties in four separate plots. Each of the four varieties (A, B, C and D) was planted just once in each row and once in each column (Figure 1). This minimized the effects of soil variation in the analysis of the plot yields.

Figure 1: Arrangment of Field Plots to Test Seed Yields

Fisher also developed the correct method for analyzing designed experiments. He called it “analysis of variance” because it breaks up the total variation in the data column into components due to different sources. Today these vector components are called “signals” and “noise.” There is a signal component for each controlled variation and a noise component representing variations not attributable to any of the controlled variations. By looking at the signal-to-noise ratio for a particular variation, the analysis of variance will provide accurate answers.

The problems Fisher encountered in conducting agricultural experiments in the 1920s exist today in virtually all Six Sigma applications. For example, industrial experimenters are confronted by significant degrees of uncontrollable variation in such areas as raw materials, human operators or environmental conditions. Such problems can be overcome by running sufficiently large experiments. Unfortunately, large experiments are often too expensive, too time consuming, or both. Fortunately, Fisher’s solutions to these problems work just as well in 21st century Six Sigma as they did in 20th century agriculture. In fact, Fisher’s methods of design and analysis have become international standards in business and applied science.

Fisher’s methods require well-structured data matrices. His analysis of variance delivers surprisingly precise results when applied to a well-structured matrix, even when the matrix is quite small.

Case Study: The Daily Grind

Don worked in the belt grinding department. Day after day, he and his co-workers removed gate stubs from metal castings to prepare them for final processing and shipping. The grinders were paid a handsome hourly rate. The other major expense was the cost of the belts. The department went through a lot of belts on a typical shift.

Define: If a belt is used beyond a certain point, the efficiency in removing metal goes way down. The supplier representative had given the area manager a rule for when the grinders should replace a worn belt. The rule was called “50 percent used up.” Examples of belts that had been 50 percent used up were hanging on the walls in the grinding department. The purpose of the rule was to minimize the total expense of the operation. Don thought the rule was wrong. He thought the rule caused them to discard the belts too soon. He had a hypothesis that using the belts a little longer would reduce the belt expense with no loss of grinding efficiency. He also suspected that the supplier just wanted to sell more belts.

LGR	Material	Usage	Grit	Session	Cost
High High High High Low Low Low Low	Rubber Rubber Steel Steel Rubber Rubber Steel Steel	50% 75% 50% 75% 50% 75% 50% 75%	50 30 30 50 30 50 30 50	AM AM AM AM AM AM AM AM	5.28 4.25 5.20 2.46 8.63 5.99 4.75 3.71
High High High High Low Low Low Low	Rubber Rubber Steel Steel Rubber Rubber Steel Steel	50% 75% 50% 75% 50% 75% 50% 75%	30 50 50 30 50 30 50 30	PM PM PM PM PM PM PM PM	6.50 4.87 3.32 2.13 8.36 4.23 5.34 2.87

Don had come up with a new rule called 75 percent used up. He proposed doing a designed experiment to determine whether or not the new rule was more cost effective than the old rule. Don, the area manager and the supplier representative discussed the project. The supplier representative was vehemently opposed to the project. He said the 50 percent rule was based on extensive experimentation and testing at his company. He said the grinding department was wasting time trying to reinvent the wheel.

Don argued that laboratory tests may not be good predictors of shop-floor performance. The area manager thought Don had a good point. He gave the go-ahead for the project. He allowed Don one full day to complete the experiment.

Measure: When the other grinders heard about the experiment, they suggested other things that could be tested in addition to the 50-versus-75-percent usage. The contact wheels currently used on the grinding tools had a low land-to-groove ratio (LGR). One of the grinders wanted to try a wheel with a higher LGR. Another wanted to try a contact wheel made out of hard rubber instead of metal (Material). A third reminded Don that belts of at least two different grit sizes were routinely used. He felt that both grits should be represented in the experiment to get realistic results (Grit).

Don figured he could get 16 castings done in one day. But he also felt that he was usually more efficient mornings than afternoons. The experiment was controlled for this by including a morning/afternoon factor in the matrix (Session). Above is the data matrix for the experiment which tested all five factors. The response variable was the total cost for each casting divided by the amount of metal removed. The total cost was calculated as labor cost plus belt cost.

Analyze: A well-designed experiment is usually easy to analyze. The data matrix suggested the following:

1. Don was on to something with his 75 percent used up

2. High LGR is better than low

3. Rubber wheels are worse than metal ones

Figure 2 shows the Pareto plot ranking the factors and their interactions in the belt grinding experiment by the strength (length) of their profit signals.

Figure 2: Pareto Plot

The strongest signal was the comparison of steel to rubber contact wheels (Material). This signal indicated that rubber was not a good idea. The next-largest signal was the comparison of the 50 percent rule to the 75 percent rule (Usage). It predicted significant savings with Don’s idea. The third-largest signal was the comparison of low to high land-to-groove ratio (LGR) for the contact wheel.

The next two signals involved interactive effects. The message here was that the actual cost reductions from implementing the Usage and LGR results would be different for the two grit sizes.

Improve: Don’s experiment produced two recommendations: 1) use his 75 percent rule instead of the supplier’s 50 percent rule and 2) use contact wheels with the higher land-to-groove ratio. The combined impact of these two changes was a predicted cost reduction of $2.75 per unit of metal removed. This amounted to about $900,000 in annual savings.

Don’s recommendations were quickly implemented throughout the grinding department. The actual savings came in a little under the prediction, but everyone was happy. Not bad for a one-day project.

Control: Some degree of cost reduction was achieved by all the grinders, but it did not apply uniformly. There was still a lot of variability in grinder performance. Attacking this variation obviously was the next step.

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DOE for Services: Right Training Makes It a Valuable Tool

When it comes to mastering design of experiments (DOE), many quality professionals experience a steep learning curve. DOE can be complex, and to fully understand and apply it, professionals need to learn when to use it, how to set up the experimental design and how to interpret their results.

Service quality professionals face an even greater challenge because they often cannot relate to the methods many instructors use to teach DOE.

Six Sigma trainers typically ask trainees to work through manufacturing-based scenarios such as identifying the ideal conditions for using a catapult to attack a castle, which can take up to a full training day or longer to execute. And because many of these Black Belts in training already believe they will never apply DOE, they do not want to spend the class time to learn it, and instructors are reluctant to make them. The challenge is to give Six Sigma trainees firsthand experience working through a designed experiment that addresses a relevant quality improvement problem and can be executed quickly. With the help of a macro (named the GO macro) written for a standard statistical software package (Minitab), here is a solution.

Training Begins with DOE Outline

DOE training for Black Belts should begin by following the outline for designing an experiment suggested by D.C. Montgomery in his book Design and Analysis of Experiments:

1. Recognition of and statement of the problem.

2. Choice of factors, levels, and ranges.*

3. Selection of the response variable.*

4. Choice of experimental design.

5. Performing the experiment.

6. Statistical analysis of the data.

7. Conclusions and recommendations.

(*In practice, Steps 2 and 3 are often done simultaneously or in reverse order.)

Also all essential DOE topics need to be covered, such as the scientific method, one factor at a time experimental approach, DOE terminology (e.g., factors, levels and response variables), screening designs, resolution, randomization, replication, analysis of variance (ANOVA), residuals, F tests, main effects and interaction plots.

The most critical part of the training, however, is to give trainees the opportunity to apply these concepts firsthand using a DOE simulation.

To accomplish this, the group of trainees should be divided into teams and given a problem statement. For example, at PricewaterhouseCoopers, one of the largest professional services firms, the problem statement that has been used is: “A professional services company has a new tax preparation service they developed for people who are 55 years or older and have ‘wealth accounts.’ The company wants you to design an experiment that will identify the direct marketing process that maximizes the number of customers they can acquire.”

Applying Concepts in DOE Simulation

Trainees are told that the response variable is the number of customers who purchase the service, then given the seven potential factors and their corresponding levels in the table below:

Factor	Description	Levels
Price	Pricing Strategy Index	90, 91,…, 109, 110
Mail Time	Weeks Since Promotional Mailer	1, 2, 3, 4, 5, 6
Sales Script	Sales Script Used for Call	A, B
Training	Prior Training on Script	Y (yes), N (no)
Gender	Gender of Caller	M (male), F (female)
Age	Age of Caller	20, 30, 40, 50, 60
Time of Day	Time of Call	D (daytime), E (evening)

The trainees’ task is to choose which factors they think may affect the number of acquired customers and determine the corresponding factor levels that they want to test. Following these steps, they are ready to choose their experimental design.

The parameters for the DOE include a budget of $40,000 and experimental runs of 100 calling hours that cost $2,000 each. Based on these parameters, there are several full factorial and fractional factorial designs that could be run within the allotted budget. For example, some students may decide there are only four potentially important factors and setup a 24 full factorial. Another group may decide they need to explore all seven factors and setup a 27-3 fractional factorial.

The Importance Is Learning about DOE

After the trainees create their experimental design, they are ready to perform the experiment. Because it is of greater valuable to spend more time learning about DOE than actually running the experiment, here is where the macro was employed to generate the response data.

The data collection process begins with the FORM worksheet in Figure 1.

Figure 1: Worksheet Trainees Use to Collect Data for Their DOE Experiment

Trainees input the factor level settings for their first run into the Condition column. If they have excluded a factor(s) from their design because they determined it was not necessary to measure it, they enter an ‘x’ for that factor(s).

After they have entered the levels for all factors, they run the macro to generate the number of corresponding customers the run would acquire after 100 calling hours. As illustrated in Figure 2, the macro:

◉ Outputs the response value to the Customers column.

◉ Transposes the specified factor levels into the Price, Mailtime, Script, Training, Gender, Age and Day columns.

◉ Tracks the cumulative amount of money spent on the runs in the $Spent column (Figure 2).

Figure 2: Worksheet After Factors Are Entered and Macro Has Generated Its Response

Macro Makes Running Experiment Easier

Trainees then repeat this process for each run of their design by entering new factor level settings into the Condition column and running the macro to generate the corresponding number of customers acquired. The macro adds the information for each run in a new row in the worksheet, and within minutes the trainees have “performed their experiments” and the data they need to evaluate their designs is ready for them to analyze (Figure 3). Columns C4 through C10 list the factor levels for each run, and C11 identifies the run number. C3 lists the number of customers acquired and C12 presents a running total of the money spent to perform the experiment.

Figure 3: A Completed Worksheet

Once the teams have conducted their analyses, they can present their findings to the entire group. The graphs they produce with their statistical software package are used to explain what factors they think significantly impacted the sales process and why (Figure 4). The learning continues as trainees discuss how they chose their experimental designs, whether they omitted important factors from the design and selected reasonable levels, and the possibility of confirmatory runs, if the budget allowed for them.

Figure 4: Interaction Plot for Acquired Customers

This approach for teaching DOE follows Montgomery’s outline and makes the process engaging for trainees. All of them understand the need to design an effective sales process, which makes it easier for them to relate to and retain the material. And the macro gives them meaningful data to work with in far less time than it would take to run a typical experiment, which leaves more time to focus on the practice of DOE itself.

Feedback on this training has been positive, with trainees frequently commenting on how the simulation brought DOE to life for them. And the benefits seem to endure. Many who entered this part of their training dismayed at having to learn something they thought they would never use, later report they are beginning to plan their own DOEs – a response that Master Black Belts everywhere can appreciate.

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Quantify the Benefits of IASSC Lean Six Sigma Certification

IASSC stands for the International Association of Lean Six Sigma Certification.

Lean Six Sigma is a methodological approach used to enhance performance by removing waste, decreasing variation, and increasing efficiency systematically. Using a mixture of lean manufacturing, lean enterprise, and Six Sigma, Lean Six Sigma aims to combat the eight several types of waste: defects, overproduction, waiting, non-utilized talent, transportation, inventory, motion, and extra processing.

The Key Benefits of IASSC Lean Six Sigma Certification

Caters to a range of abilities: As earlier mentioned, the IASSC offers three different certifications; Black Belt, Green Belt, and Yellow Belt. Depending on your experience, knowledge, and skill level, there is an entry-level available for all professionals looking to succeed using the Lean Six Sigma methodology.

Process Development Career Opportunities:

• IASSC Lean Six Sigma certifications are well suited to;
• Having Lean Six Sigma certification in your achievements gives you a powerful boost to your career.
• Applying the methodologies taught in Lean Six Sigma presents a firm promise to the organization or business you are involved in.
• It assists you in solving core management issues and improve efficiency.

1. Expert Success with IASSC Lean Six Sigma Certification:

The most known thought process to have a certification is to advance in your profession. Having Lean Six Sigma certification gives underwriting to businesses that you have a straightforward range of abilities. Being certified shows that you can implement Lean Six Sigma concepts and stand out from the crowd.

2. Recognized as a Leader:

When you do Lean Six Sigma certification, you will have a non-exhaustive grip of thinking processes. Also, an ability to measure financial services for the same. And you will be seen as a leader in a team. The learned strategies and the ability to complete Lean Six Sigma tools help improve the business model's productivity.

Individuals who are Lean Six Sigma Black Belt are additionally prepared to take in a change. They assist in process improvement, quality control, which ultimately leads to financial benefits to the clients.

3. Completion in Career with IASSC Lean Six Sigma Certification:

Finance management and issue evaluation are alluring abilities for an organization. These key characteristics are seen as growth metrics in a company. Certified Lean Six Sigma experts get fast growth in the government and ultimately get higher positions with no doubt.

4. Real Problem Solver:

A genuine Lean Six Sigma certification serves to achieve more for an organization. It helps you as an individual to handle processes. Individuals who understand and are trained in Lean Six Sigma voice a qualified language. They better know how crucial is the situation and implement Lean Six Sigma methodologies to fix a process and decrease waste. Which ultimately reduces costs.

5. Improve Business Processes:

When you get the Lean Six Sigma certification, you will have the capacity to show that you have the right analytical skills to measure, break down, control, and change. You will have the ability to survey the modern procedures. You will pick up correct information about their impact on quality execution.

You will develop the capacity to accomplish the dimension of continuous quality improvement that the company wants. You will most likely watch forms near repeat; there is no difference from the mean. You will almost absolutely take the right measures in a task.

6. Excellent Salary:

Like any other profession, Lean Six Sigma salaries are also reliant on many factors such as when one becomes certified as Green Belt or Black Belt and the number of projects, overall years of experience, cultural background, and previous experience has an impression. Hence it makes it more complex to arrive at an average salary range.

A lot can change each way based on the effect created by their respective projects. When someone gets into discussing roles, compensation is even more difficult with the addition of many other factors coming into play.

7. Be Relevant Across Industries:

What are the benefits of Lean Six Sigma certification? Lean Six Sigma method is not only applied in the manufacturing industry but also other sectors like aviation, IT, telecom, agriculture, and a lot more. Getting a Lean Six Sigma certification can help better employment prospects.

You will see hints of improvement in your compensation. Lean Six Sigma tests are difficult to pass. This is one reason Lean Six Sigma certified experts get so much admiration. Officials and employing managers at key organizations are very much aware of this reality.

8. Streamline Businesses:

Lean Six Sigma certified professionals would certainly distinguish themselves as a specialist inside the organization. You will receive quality improvement all through the organization. You will fortify your authority characteristics. People certified in Lean Six Sigma are educated in various strategies to streamline business forms.

IASSC Certified Lean Six Sigma experts will be specialists in reducing expenses and expanding income. This leads to a superior main concern, despite the industry. As an expert, you have to adjust to the changing requirements of your industry. You have to think out how to update your insight into various things, regardless of what industry you are part of.

9. Guarantee Compliance:

With actual knowledge of the principles of Lean Six Sigma. Process errors are decreased to irrelevant numbers. This implies that numerous companies apply Lean Six Sigma while assessing the process. As a certified Lean Six Sigma expert, you will almost certainly help companies comply with universal principles, which ultimately leads to customer satisfaction.

10. Get Hands-On Experience:

Lean Six Sigma certification includes projects which give hands-on experience on how business venture works. It provides a simulation with individual circumstances. As a certified Lean Six Sigma expert, you will have an adventure even before entering the industry.

11. More Real Understanding:

Numerous experts have what it takes and carry out the responsibility as someone who is certified. Formal preparation and certification give an edge. It allows you to apply the strategy successfully. Individuals who are not familiar with Lean or Six Sigma may not be able to recognize and fix issues. They might not have the idea of what an argument looks like. At this point, the certified ones have explicit knowledge of the processes and might upgrade the current processes.

12. Authoritative Growth:

Applying Lean Six Sigma is a recognized method for developing a company. An organization requires such individuals who are prepared and comprehend the techniques. For such organizations with certified personnel, it is simpler to drive activities and new tasks intended to change forms. A company can reach its objectives by taking out waste and move ahead on its competitors.

13. Increase Organization:

From a venture's viewpoint, accomplishing an IASSC Lean Six Sigma certification empowers people to understand the fundamentals. The individual performs the capacity to distinguish and reduce repeatable errors. People with a Lean Six Sigma certification would most likely grow a company to successful ones. Because, as an individual, you will most likely understand and lessen the mistakes. And these errors would have cost the company to lose a long term client.

14. Change Company Culture:

Lean Six Sigma is a built-up system. It has become a culture of huge companies. Everybody in such a company can adjust to change and adapt to push forward the organization. Having an improvement in literature is the thing that will genuinely support an organization. Culture spreads from the best. Pioneers require to receive a nonstop improvement culture to strengthen it all through the organization. By having experts who are certified, can introduce the right lifestyle that can be very much welcomed.

15. Eliminate Errors in Organization:

Securing Lean Six Sigma certification abilities empowers a person to exhibit continuous endeavors from a company's point of view. And increase steady and expected procedure results that are essential to a company's general improvement. Most people with this certification are necessary to the company's capacity to distinguish and take out repeatable procedure mistakes. With a Lean Six Sigma certification, you can see and reduce errors.

Read: Become a Qualified Leader with IASSC Lean Six Sigma Certification and How Important to Consider One

16. Adapt to Methods:

Furthermore, an IASSC Lean Six Sigma certification encourages you to adapt to different methodologies easily like kaizen. It is described systems to accomplish quicker than-anticipated upgrades to the procedure or item. In the IT industry, certified Lean Six Sigma experts could help reduce invoicing mistakes, client grievances, objection goals, time, IT spending, stops, and cost.

17. Project Management:

As a Lean Six Sigma certified, you would be able to manage many projects. Because you will have the ability to prioritize the tasks, therefore, you will have the ability to make the projects simpler for them to work on.

Conclusion

There are three levels of IASSC Lean Six Sigma certification, yellow belt, green belt, and black belt certification. Take the right certification at every stage of your career and get ahead of the crowd.

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Six Sigma DMAIC Quick Reference

The DMAIC methodology should be used when a product or process is in existence at your company but is not meeting customer specification or is not performing adequately. For DMAIC milestone reviews, there are certain deliverables, checkpoints, questions and concerns that the Black Belt and improvement team should be aware of prior to a tollgate/milestone review.

In lieu of or in addition to your Master Black Belt tollgate/milestone preparation review, the following Six Sigma DMAIC quick reference sheets can help prepare for your milestone review.

Jump to: Define, Measure, Analyze, Improve, Control

Define Phase

Deliverables Of Phase:

◉ Fully trained team is formed, supported, and committed to work on improvement project.
◉ Customers identified and high impact characteristics (CTQs) defined, team charter developed, business process mapped.

Checkpoints For Completion:

Team Readiness

◉ Team is sponsored by a champion or business leader.
◉ Team formed and team leaders (MBBs/Coaches and BBs/Project Leads) assigned.
◉ Improvement team members fully trained on Six Sigma and DMAIC.
◉ Full participation by members in regularly held team meetings.
◉ Team members perform project work when assigned and in a timely fashion.
◉ Team members regularly document their project work.
◉ Team is equipped with available and reliable resources.

Customers (and CTQs)

◉ Customer(s) identified and segmented according to their different needs and requirements.
◉ Data collected and displayed to better understand customer(s) critical needs and requirements.

Team Charter

◉ Project management charter, including business case, problem and goal statements, project scope, milestones, roles and responsibilities, communication plan.

Business Process Mapping

◉ Completed, verified, and validated high-level ‘as is’ (not ‘should be’ or ‘could be’) business process map.
◉ Completed SIPOC representation, describing the Suppliers, Inputs, Process, Outputs, and Customers.

Questions To Determine Appropriate Application:

Team Readiness

◉ Who are the improvement project team members, including BBs/Project Leads and MBBs/Coaches?
◉ Has everyone on the team, including the team leaders, been properly trained (on DMAIC)?
◉ Does the team have regular meetings?
◉ How often are the team meetings?
◉ Is there regularly 100% attendance at the team meetings? If not, have appointed substitutes attended to preserve cross-functionality and full representation?
◉ If substitutes have been appointed, have they been briefed on the project charter and goals and received regular communications as to the project’s progress to date?
◉ Has the project work been fairly and/or equitably divided and delegated among team members who are qualified and capable to perform the work? Has everyone contributed?
◉ Are there any constraints known that bear on the ability to perform project work? How is the team addressing them?
◉ How is the team tracking and documenting its work?
◉ Is the team adequately staffed with the desired cross-functionality? If not, what additional resources are available to the team?

Customers (and CTQs)

◉ Has the customer(s) been identified?
◉ Are there different segments of customers?
◉ Has the improvement team collected the ‘voice of the customer’ (obtained feedback – qualitative and quantitative)?
◉ What customer feedback methods were used to solicit their input?
◉ Have the customer needs been translated into specific, measurable requirements? How?

Team Charter

◉ Has a team charter been developed and communicated?
◉ Has the charter changed at all during the course of the project? If so, when did it change and why?
◉ Does the charter include the following?

– Business Case: What are the compelling business reasons for embarking on this project? Is the project linked to key business goals and objectives? What key business process output measure(s) will the project leverage and how? What are the rough order estimates on cost savings/opportunities on this project?

– Problem Statement: What specifically is the problem? Where does it occur? When does it occur? What is its extent?

– Goal Statement: What is the goal or target for the improvement team’s project? Do the problem and goal statements meet the SMART criteria (specific, measurable, attainable, relevant, and time-bound)? Has anyone else (internal or external to the organization) attempted to solve this problem or a similar one before? If so, what knowledge can be leveraged from these previous efforts? How will the project team and the organization measure complete success for this project?

– Roles and Responsibilities: What are they for each team member and its leadership? Where is this documented?

– Project Scope: What are the boundaries of the scope? What is in bounds and what is not? What is the start point? What is the stop point? How does the project manager ensure against scope creep? Is the project scope manageable? What constraints exist that might impact the team?

– Milestones: When was the project start date? When is the estimated completion date? Is the project currently on schedule according to the plan? Has a project plan, Gantt chart, or similar been developed/completed? How did the project manager receive input to the development of the plan and the estimated completion dates/times of each activity? Is there a critical path to complete the project? How will variation in the actual durations of each activity be dealt with to ensure that the expected project completion date is met?

– Communication Plan: What are the dynamics of the communication plan? What critical content must be communicated – who, what, when, where, and how? When are meeting minutes sent out? Who is on the distribution list? How do you keep key subject matter experts in the loop?

Business Process Mapping

◉ Has a high-level ‘as is’ process map been completed, verified and validated?
◉ Has a SIPOC diagram been produced describing the Suppliers, Inputs, Process, Outputs, and Customers?
◉ Is the improvement team aware of the different versions of a process: what they think it is vs. what it actually is vs. what it should be vs. what it could be?
◉ Is the current ‘as is’ process being followed? If not, what are the discrepancies?
◉ Are different versions of process maps needed to account for the different types of inputs?
◉ How was the ‘as is’ process map developed, reviewed, verified and validated?
◉ What tools and roadmaps did you use for getting through the Define phase?

Measure Phase

Deliverables Of Phase:

Key measures identified, data collection planned and executed, process variation displayed and communicated, performance baselined, sigma level calculated.

Checkpoints For Completion:

Key Measures Identified

◉ Key measures identified and agreed upon.
◉ High impact defects defined and identified in the business process.

Data Collection Planned and Executed

◉ Solid data collection plan established that includes measurement systems analysis.
◉ Data collected on key measures that were identified.

Process Variation Displayed/Communicated

◉ Process variation components displayed/communicated using suitable charts, graphs, plots.
◉ Long term and short term variability accounted for.

Performance Baseline/Sigma Calculation

◉ Measure baseline process performance (capability, yield, sigma level).

Questions To Determine Appropriate Application:

Key Measures Identified

◉ What are the key input variables? What the key process variables? What are the key output variables?
◉ What key measures identified indicate the performance of the business process?
◉ What are the agreed upon definitions of the high impact characteristics (CTQs), defect(s), unit(s), and opportunities that will figure into the sigma calculations and process capability metrics?

Data Collection Planning and Execution

◉ Was a data collection plan established?
◉ What data was collected (past, present, future/ongoing)?
◉ Who participated in the data collection?
◉ How did the team select a sample?
◉ What has the team done to assure the stability and accuracy of the measurement process?
◉ Was a gauge R&R conducted?
◉ Was stratification needed in the data collection and analysis?

Process Variation Displayed/Communicated

◉ What charts has the team used to display the components of variation in the process?
◉ What does the chart tell us in terms of variation?

Performance Baseline/Sigma Calculation

◉ What is the current process performance in terms of it capability indices?
◉ What is the current process performance in terms of its yield or sigma level(s)?
◉ How large is the gap between current performance and the customer-specified (goal) performance?
◉ Have you found any ‘ground fruit’ or ‘low-hanging fruit’ for immediate remedies to the gap in performance?
◉ What particular quality tools did the team find helpful in getting through the measure phase?

Analyze Phase

Deliverables Of Phase:

Data and process analysis, root cause analysis, quantifying the gap/opportunity.

Checkpoints For Completion:

Data and Process Analysis

◉ Identify gaps between current performance and the goal performance.

Root Cause Analysis

◉ Generate list of possible causes (sources of variation).
◉ Segment and stratify possible causes (sources of variation).
◉ Prioritize list of ‘vital few’ causes (key sources of variation).
◉ Verify and quantify the root causes of variation.

Quantifying the Gap/Opportunity

◉ Determine the performance gap.
◉ Display and communicate the gap/opportunity in financial terms.

Questions To Determine Appropriate Application:

Data and Process Analysis

◉ What does the data say about the performance of the business process?
◉ Did any value-added analysis or ‘lean thinking’ take place to identify some of the gaps shown on the ‘as is’ process map?
◉ Was a detailed process map created to amplify critical steps of the ‘as is’ business process?
◉ How was the map generated, verified, and validated?
◉ What did the team gain from developing a sub-process map?
◉ What were the crucial ‘moments of truth’ on the map?
◉ Were there any cycle time improvement opportunities identified from the process analysis?
◉ Were any designed experiments used to generate additional insight into the data analysis?
◉ Did any additional data need to be collected?
◉ What model would best explain the behavior of output variables in relation to input variables?

Root Cause Analysis

◉ What tools were used to generate the list of possible causes?
◉ Was a cause-and-effect diagram used to explore the different types of causes (or sources of variation)?
◉ What tools were used to narrow the list of possible causes?
◉ Were Pareto charts (or similar) used to portray the ‘heavy hitters’ (or key sources of variation)?
◉ What conclusions were drawn from the team’s data collection and analysis?
◉ How did the team reach these conclusions?

Quantifying the Gap/Opportunity

◉ What is the cost of poor quality as supported by the team’s analysis?
◉ Is the process severely broken such that a re-design is necessary?
◉ Would this project lend itself to a DFSS project?
◉ What are the revised rough order estimates of the financial savings/opportunity for the improvement project?
◉ Have the problem and goal statements been updated to reflect the additional knowledge gained from the analyze phase?
◉ Have any additional benefits been identified that will result from closing all or most of the gaps?
◉ What were the financial benefits resulting from any ‘ground fruit or low-hanging fruit’ (quick fixes)?
◉ What quality tools were used to get through the analyze phase?

Improve Phase

Deliverables Of Phase:

Generate (and test) possible solutions, select the best solutions, design implementation plan.

Checkpoints For Completion:

Generating (and Testing) Possible Solutions

◉ Possible solutions generated and tested.

Selecting The Best Solution(s)

◉ Optimal solution selected based on testing and analysis.
◉ New and improved process (‘should be’) maps developed.
◉ Cost/benefit analysis of optimal solution(s).
◉ Small-scale pilot for proposed improvement(s).
◉ Pilot data collected and analyzed.
◉ Improved process (‘should be’) maps modified based on pilot data and analysis.
◉ Project impact on utilizing the best solution(s).

Designing Implementation Plan

◉ Solution implementation plan established, including schedule/work breakdown structure, resources, risk management plan, cost/budget, and control plan.
◉ Contingency plan established.

Questions To Determine Appropriate Application:

Generating (And Testing) Possible Solutions

◉ How did the team generate the list of possible solutions?
◉ What tools were used to tap into the creativity and encourage ‘outside the box’ thinking?

Selecting The Best Solution(s)

◉ What tools were used to evaluate the potential solutions?
◉ Were any criteria developed to assist the team in testing and evaluating potential solutions?
◉ What were the underlying assumptions on the cost-benefit analysis?
◉ Are there any constraints (technical, political, cultural, or otherwise) that would inhibit certain solutions?
◉ Was a pilot designed for the proposed solution(s)?
◉ Describe the design of the pilot and what tests were conducted, if any?
◉ What conclusions were drawn from the outcomes of the pilot?
◉ What lessons, if any, from the pilot were incorporated into the design of the full-scale solution?

Designing The Implementation Plan

◉ Is the improvement plan best served by using the DFSS approach?
◉ What is the implementation plan?
◉ What poka-yoke or error proofing will be done to address some of the discrepancies observed in the ‘as is’ process?
◉ What does the ‘should be’ process map/design look like?
◉ How does the solution remove the key sources of variation discovered in the analyze phase?
◉ What attendant changes will need to be made to ensure that the solution is successful?
◉ What communications are necessary to support the implementation of the solution?
◉ How will the team or the process owner(s) monitor the implementation plan to see that it is working as intended?
◉ What is the team’s contingency plan for potential problems occurring in implementation?
◉ How will the organization know that the solution worked?
◉ What tools were most useful during the improve phase?

Control Phase

Deliverables Of Phase:

Documented and implemented monitoring plan, standardized process, documented procedures, response plan established and deployed, transfer of ownership (project closure).

Checkpoints For Completion:

Monitoring Plan

◉ Control plan in place for sustaining improvements (short and long-term).

Process Standardization

New process steps, standards, and documentation are ingrained into normal operations.

Documented Procedures

◉ Operating procedures are consistent.
◉ Knowledge gained on process is shared and institutionalized.

Response Plan

◉ Response plans established, understood, and deployed.

Transfer of Ownership (Project Closure)

◉ Transfer ownership and knowledge to process owner and process team tasked with the responsibilities.

Questions To Determine Appropriate Application:

Monitoring Plan

◉ What is the control/monitoring plan?
◉ How will the process owner and team be able to hold the gains?
◉ What key inputs and outputs are being measured on an ongoing basis?
◉ How will input, process, and output variables be checked to detect for sub-optimal conditions?
◉ How will new or emerging customer needs/requirements be checked/communicated to orient the process toward meeting the new specifications and continually reducing variation?
◉ Are control charts being used or needed?
◉ How will control chart readings and control chart limits be checked to effectively monitor performance?
◉ Will any special training be provided for control chart interpretation?
◉ Is this knowledge imbedded in the response plan?
◉ What is the most recent process yield (or sigma calculation)?
◉ Does the process performance meet the customer’s requirements?

Process Standardization

◉ Has the improved process and its steps been standardized?

Documented Procedures

◉ Is there documentation that will support the successful operation of the improvement?
◉ Does job training on the documented procedures need to be part of the process team’s education and training?
◉ Have new or revised work instructions resulted?
◉ Are they clear and easy to follow for the operators?

Response Plan

◉ Is a response plan in place for when the input, process, or output measures indicate an ‘out-of-control’ condition?
◉ What are the critical parameters to watch?
◉ Does the response plan contain a definite closed loop continual improvement scheme (e.g., plan-do-check-act)?
◉ Are suggested corrective/restorative actions indicated on the response plan for known causes to problems that might surface?
◉ Does a troubleshooting guide exist or is it needed?

Transfer Of Ownership (Project Closure)

◉ Who is the process owner?
◉ How will the day-to-day responsibilities for monitoring and continual improvement be transferred from the improvement team to the process owner?
◉ How will the process owner verify improvement in present and future sigma levels, process capabilities?
◉ Is there a recommended audit plan for routine surveillance inspections of the DMAIC project’s gains?
◉ What is the recommended frequency of auditing?
◉ What should the next improvement project be that is related to the process?
◉ What quality tools were useful in the control phase?

Integrating and Institutionalizing Improvements, Knowledge and Learnings

◉ What other areas of the organization might benefit from the project team’s improvements, knowledge, and learning?
◉ How might the organization capture best practices and lessons learned so as to leverage improvements across the business?
◉ What other systems, operations, processes, and infrastructures (hiring practices, staffing, training, incentives/rewards, metrics/dashboards/scorecards, etc.) need updates, additions, changes, or deletions in order to facilitate knowledge transfer and improvements?

Source: isixsigma.com

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The Implementation Plan – Getting Beyond the Quick Fix

One of my favorite elements of Six Sigma is researching a problem and finding the data to justify making an improvement. However, this element can also be one of the biggest barriers to securing support for a Six Sigma program. While practitioners might enjoy the hunt, executives often are looking for quick solutions that can be implemented immediately. They may not be interested in spending the time to research a problem for the true solution.

This rush for solutions can be addressed through coaching. With the introduction of Six Sigma, executives and project managers should be coached to spend more time at the front-end of the project in the Define, Measure and Analyze phases. But a word of caution: Having coached several projects, I have witnessed incidents proving that “more time” can quickly become too much time. Suddenly projects fall behind deadline, forcing implementation to be rushed. Therefore, proper planning of the key elements of solution implementation is needed so that practitioners can avoid a time crunch.

Implementing Solutions

Implementation involves executing the process improvements that have been developed throughout the life of the project. There are key elements of any implementation that primarily include planning: planning the work, planning the tasks and subtasks, planning the time, and planning the people and resources. To these planning elements must be added an understanding step; that is, understanding the “why” and understanding whether or not the project worked.

A thorough implementation plan usually covers at least five elements: The work plan, resources and budget, stakeholders, risk assessment, and quality control.

The Work Plan

The basic objective of any work plan is to establish and communicate what is going to happen and when to ensure that all involved have a common understanding of how the improvements will be implemented. The work plan identifies the changes needed for existing processes, procedures, resources and equipment, and documents how to make the changes. In addition, the plan identifies who will make the changes and when they will be completed. It is also crucial to determine how the changes will be measured and deemed successful.

Resources and Budget

If the implementation of the solution requires significant time, staff additions or other resources, sponsors may want that information included in the implementation plan. Some software programs can automatically generate resource usage charts.

It’s a good idea to determine the budget components that should be captured (salaries, incremental costs, etc.) with managers. Practitioners should also check when and how managers want budget information and if there are particular accounting codes that must be used.

A few questions to think about are: What dollars and other expenses are needed to get the job done? When the overall implementation budget has been approved, how will it be allocated? Often, practitioners will need to indicate categories for the rate at which expenses accrue (such as hourly rate for subcontractors) and for total projected expenses (Table 1). Typical budget categories may include: materials or supplies; telephone/Internet/fax charges; equipment rental or purchase; staff expenses; travel; subcontractors; legal expenses; shipping charges; and photocopying.

Table 1: Sample Budget and Resources

Category	Rate	Total	Resource	Planning
Travel	3 trips @ $2,000/trip	$6,000	Project Office	20 hrs./wk., starting 7/1 thru 9/30
Legal	10 hrs. @ $350/hr.	$3,500	Bryan & Tracee	20 hrs./wk. for 4 wks.
Sub-contractors	40 hrs. @ $125/hr.	$5,000	3 sub-contractors	Obtain resumes from pool by 6/1
Materials/supplies		$340	Jared & Jeff	40 hrs./wk. for 5 wks.
Total		$14,840

Stakeholders

Stakeholders are the people who will be affected by the project or who can influence it. Examples are managers, process owners, people who work with the process under study, internal departments that support the process, customers, suppliers and the financial department.

A stakeholder analysis tool is often used to identify and enlist support from stakeholders (Figure 1). It provides a visual means of identifying stakeholder support, which can ease the creation of an action plan for the project. It helps the team begin to discover ways to influence relationships and strategies to ensure that the project has the appropriate involvement and support from the key stakeholders. Most important, it helps the team answer the question, “Where does this stakeholder currently stand on the issues/ impact associated with this effort?”

Figure 1: Stakeholder Analysis Tool

The following are the five major steps in conducting an analysis of the stakeholders and possible resistance:

1. Identify stakeholders (people or groups). Stakeholders’ interest in the project is twofold: They either influence the change or are affected by the change. Either way, stakeholders are uniquely positioned to help or hinder implementation of the change.

2. Indicate current and needed levels of commitment. The objective of this step is to answer the following: Who are the stakeholders? Where do they currently stand in terms of support of or resistance to the project? What level of support can be expected from them?

3. Identify potential reasons for resistance. Resistance analysis is meant to help the team to understand the nature of resistance that they may face while completing a project and to develop a strategy for overcoming it. It is also important to identify the root cause of the resistance.

4. Develop action plans aimed at reducing or eliminating resistance. These plans are essential in minimizing the potential negative implications.

5. Indicate responsible party and target dates for action plan initiatives. Document who is responsible for completing each of the action plans, with clearly established target dates. Make sure the project plan schedules this task to be completed at the beginning of the project as well as in the implementation stage.

Risk Assessment

In short, risk assessment involves the project team identifying all potential risks of the project implementation and communicating them to the Champion and stakeholders. There are several variations of a risk analysis, but the majority of the templates available call for the same steps:

◉ Brainstorm all potential risks that might decrease the probability of successful project completion.

◉ Assign a scale (high-medium-low) to both the probability and impact of each potential risk. Multiply combined probability and risk to get total risk.

◉ Identify activities that need to occur to mitigate risk and ensure that a contingency plan is in place. Owners should be assigned to both plans.

Make sure that sponsors and key stakeholders are kept up to date about the risks identified and how they will impact the implementation (Table 2). An additional risk question would be to examine what might derail any team members when trying to implement the team’s great ideas. Examples include cost, organizational changes, competing projects, new technology, politics and resource availability.

Table 2: Risk Sources and Categories to Consider

Sources of Risk	Risk Categories
Business Case ◉ Cost increase ◉ ROI lead time increase ◉ changing market/regultory environment ◉ business commitment	Product/Service Design ◉ Porduct performance ◉ Product/service cost ◉ Business buy-in
Planning ◉ Resource availability ◉ Project complexity ◉ Developement time ◉ Project management experience	Quality ◉ Accuracy in VOC ◉ Process Capability ◉ Process/service sigma levels
Organizational ◉ Cross-functional involvement ◉ Process ownership ◉ Multiple locations for implementation ◉ Change management issues	Operations ◉ Investment and operating costs ◉ Process scaling factor ◉ Process control capability ◉ Vendor quality ◉ Speed and responsiveness
Technical ◉ Technology experience ◉ Design complexity ◉ Scope changes ◉ Knowledge of business processes ◉ Quality methods, skills ane experience	Legal ◉ Regulatory requirements (SEC, etc.) ◉ Privacy, contracts, etc.
External ◉ Vendor/contractor experience and support ◉ Multiple vendors/contractors	Program management ◉ Program resources ◉ Program cost ◉ Schedule and project tracking
	Other ◉ Business-specific ◉ Change management/adoption ◉ Human resources

After identifying these risks, practitioners should try to overlay these issues against the stakeholder analysis and process maps to see how these tools are impacted and what should be the next steps.

Quality Control

Quality control is a process by which entities review the quality of all factors involved in production. This approach places an emphasis on three aspects:

1. Hard elements, such as controls; job management; defined and well-managed processes; performance and integrity criteria; and identification of records

2. Competence, such as knowledge, skills, experience and qualifications

3. Soft elements, such as personnel integrity, confidence, organizational culture, motivation, team spirit and quality relationships

In this instance, quality control relates to project management, which requires the project manager and the project team to inspect the accomplished work to ensure that it is aligned with the project scope and that changes are sustained. Dashboards present a great picture to assist with success measurement. These dashboards can include control charts, run charts, histograms, Pareto charts and bar charts (Figure 2).

Figure 2: Example of Dashboard

A few of the quality control efforts should take place at the beginning of a project, such as the determination of the key reactive and proactive metrics the sponsor will want to review. My company’s best practice has been to begin the design and development of dashboards during the Define and Measure stages of the project. This can be as simple as creating a one-page document (more if necessary) that demonstrates how the team will present each metric (e.g., run chart, Excel table, etc.) Please note that each metric should tie to a critical-to-quality factor (CTQ). A good rule of thumb to remember is that more is not necessarily better – showing the key metrics only should suffice.

Practitioners should facilitate preliminary discussions with the sponsor explaining how these metrics will replace current reports so that the team is not simply creating more work. It may be preferable to provide a high-level dashboard for the sponsor and a more detailed one for the process owner. Practitioners also should gain sponsor and process owner agreement that these are the right metrics and the right format for the dashboard. After implementation, they should collect data so that an actual dashboard can be presented at the project’s report-out or tollgate reviews.

Increasing Odds of Success

Implementation planning will help ensure that the right resources and stakeholders are involved to execute the implementation plan in order to meet or exceed target dates. Proper planning increases a project’s odds to be on time, in scope and within budget implementation. If variations take place they can be easily accounted for with few surprises.

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Remember Common Cause Variation in Fight Against Process Waste

Ideally, practitioners want an error rate to be at 0 percent. But if an error rate is steadily hovering at about 2 percent, it is fair to say that the errors are due to common cause variation. If the error rate suddenly surges beyond its usual level, however, it is probably due to some change to the product, such as variations in material, workmanship or test codes. This change is called special cause variation.

Practitioners typically approach these forms of variation differently, with special cause variation taking priority. But it may be profitable for practitioners and company leaders to reconsider their focus and pay closer attention to variation stemming from common causes.

Giving Attention to Variation

In most situations, special cause variation captures the attention of the management team because this form of manufacturing waste is not budgeted for in the accounting book.

Typically, companies allocate a certain amount of money for manufacturing waste. The amount is based on past performance. When special cause events – which are usually not forecasted – occur, they can drastically affect certain business transactions, such as fulfilling a customer’s order, and can eat into the money budgeted for waste. Therefore, much effort and attention is put into resolving special cause events when they occur.

Contrarily, common cause variation is a known variation that is due to process noise and is typically inherited from the first day of production. Furthermore, the manufacturing waste generated from common cause variation is predictable, meaning it is usually budgeted for. As such, it may get less attention as compared to special cause events.

Reconsidering Waste

Although special cause variation may be the main focus, common cause variation is consistently contributing to manufacturing waste. It is generated from sources such as rework, retesting and scrap, and this waste is a cost to the business. For instance, rework cost is incurred by labor, material and transport logistics, and retesting incurs labor cost and takes up tester capacity. These costs affect the organization’s profitability.

The Real Cost of Common Cause Variation

The following example illustrates the importance of paying attention to common cause variation. In this case, the error rate of a test station is consistently hovering at about 2 percent.

If 2 percent of products go for rework, additional labor will be needed to work on them. which is an additional cost to the business. On the other hand, if the defective products are retested, it will take up 2 percent of the tester’s capacity. Hence, the company may need to buy additional testers in order meet total shipment requirements. If the 2 percent of products that fail at the test station are scrapped, then the money has gone down the drain.

Despite common cause variation maintaining its 2 percent level, the production volume goes up, and the number of defects also will go up proportionally. This rise in products that fail testing requires more money allocated for additional equipment, labor, testers and other supporting tools. Again, these additional costs eat into the profitability of a company.

Practitioners also should be considering the snowball effect from the defects generated by common cause variation. For instance, if the deposition of a rework or retest is not clearly defined, the defective products will continuously loop within the test processes. A reasonable number of cycles must be established for reworking and retesting for each failed unit. Apart from incurring additional costs and testing capacity, the snowball effect may generate other negative outcomes, such as taking up storage capacity.

This scenario is based on a single error code. If the manufacturing process has multiple error codes and each error code has its own common cause variation, the waste generated can be quite significant.

Fighting Variations to Stay Competitive

Lean methodology states that retesting, rework, unnecessary movement and inventory pileup are part of manufacturing waste. Therefore, effort to reduce costs due to such waste generated from common cause variation is essential.

In order to stay competitive in today’s market, practitioners must do more than fire fight special cause events – they must thoroughly investigate the sources of common cause variation.

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Optimizing OR Capacity at The Children’s Hospital

Perioperative services is one of the most challenging and complex environments in healthcare. It is often prone to variability in terms of processes, patient volume and case type. Bottlenecks, delays and problems with patient flow frequently surface in this critical area, impeding the organization’s ability to manage the daily caseload and capacity allocation.

To increase operational efficiency and access within its perioperative department, The Children’s Hospital in Denver, Colorado, USA, began a focused improvement initiative in 2005. The hospital sought to address patient throughput, enhance service delivery and implement control mechanisms for continuous process monitoring. It also wanted to make sure that improvements would be transferable to the new hospital being built to accommodate population growth and technology advances.

The project at The Children’s Hospital targeted the following primary areas:

◉ Block schedule

◉ Room turnover

◉ Delays

◉ First case starts

◉ Pre-op process

◉ Urgent room

◉ Adds-ons

Identifying Issues and Solutions

The project team began by gathering information, evaluating the current state and defining the reasons for delays. In terms of improving service delivery, the project goals included increasing the amount of unblocked time available, reducing case start delays, improving room turnover time, increasing the number of on-time first case starts and creating a new pre-op process. The initial data collection and analysis revealed significant opportunities for improvement. Regarding the first surgical case of the day, for instance, the team found that delays were occurring 80 percent of the time.

After reviewing and sharing its findings, the team began developing solutions through strategies such as change acceleration process (CAP), Work-Out, Lean, Six Sigma and computer-based simulation and constraint management models. Each method was selected based on the type of challenge presented during the course of the project. CAP played a significant role in meetings, particularly in gaining physician buy-in. Six Sigma methods were employed when the situation required statistical analysis, while Lean techniques were used to address process issues. Simulation modeling helped assess the design of the new pre-op process and block scheduling constraint modeling aided the development of a new surgeon-specific block schedule that opened additional open operating room (OR) time for new business.

The hospital’s chief surgery officer, Dr. Mory Ziegler, noted the importance of the process both in terms of instituting meaningful change and in providing a broader learning opportunity for staff. “Having access to credible data has been useful to either disprove or validate our observations,” Dr. Ziegler said. “I was also pleasantly surprised to find that there was much greater participation on the part of physicians than I had anticipated.”

Success in Making Improvements

Solutions included four-hour blocks to improve efficiency, surgeon-specific blocks to drive accountability, limited one room use in some cases and a block management policy. The team also recommended staffing the department with two schedulers to better align with the physicians’ office hours. A “blast fax” announced available OR times to surgeons’ offices, and a daily OR schedule also was delivered by fax. New standard procedures for room turnover were put in place, and a new “room ready” cycle (wheels out to room ready) was introduced.

To minimize first case start delays, a pre-op clinic and 5:30 a.m. first case arrival policy were implemented. Standard operating procedures (SOPs) would include education and orientation for new staff. A governance structure was created with a steering committee for ongoing process review, and a perioperative services dashboard was developed for continuous process monitoring and improvement. For add-on cases, the schedule office now takes next day cases until 3 p.m.

Other improvements which came from the project team include:

◉ Discipline-specific SOPs in the OR

◉ Timeline for each discipline in the pre-op process

◉ Checklist for patient ready and time log for each step of pre-op process

◉ NPO compliance and tracking of delay

◉ Updated urgent room policy

◉ Centralized admissions

◉ Development of anesthesia inventory list

Evaluating the Project’s Impact

Following implementation of recommended solutions, the results of the perioperative project were quantified and are being tracked closely through control mechanisms. Delays have been reduced by 7 percent; room turnover time has improved by 9 percent; and on-time first case starts have increased by 26 percent.

Based on evaluation of the data and application of a constraint management block scheduling solver, improvements in the block scheduling process should allow The Children’s Hospital to accommodate five additional cases per week. Changes included revising the schedule to add 9.05 hours of unblocked time per week, which expanded capacity for surgeons that formerly had difficulty accessing the operating room. This represents a potentially significant financial impact for the hospital. Applying an average margin per case of $2,000, the projected annual benefit of capturing five additional cases per week would be $520,000. The following results were measured in March 2006 and improvements have been sustained.

The Children’s Hospital Perioperative Project Results

Metric	Baseline	Re-Measure	Improvement
Unblock Time (Hour/Week)	54.95	60.00	9.05
Room Turnover (Average Minutes)	34	31	3
Delays: Percent of Cases Not Starting on Time	52%	45%	7%
First Case Starts: Percent of Cases Starting on Time	20%	46%	26%
Adds-On Cases: Percent Added to Schedule After Close	44%	17%	27%
Note: Baseline data from July 2004-July 2005; Re-measure data from March 2006

“We went live with the changes in March 2006, and saw substantial improvement in all metrics we were tracking within the five-month time period from March to September,” Dr. Ziegler said. “We also had a larger case volume during this timeframe, which may have caused the numbers to level off somewhat – though they are still better than they were when we started the project. I would attribute some of the volume growth we’ve seen to the process improvements that were implemented, which have allowed us to expand capacity and schedule additional cases for surgery.”

 Dr. Ziegler also noted that during this same timeframe, the organization was in the process of converting to an electronic health record. This naturally created a certain amount of additional activity for staff and clinicians.

“Personally, I’m not worried about fluctuations. We’re trying to make this part of our new culture. In general, this project enabled us to achieve measurable results, and it was a positive learning experience for our staff,” Dr. Ziegler said.

Hospital Project Key Indicators

◉ Unblocked time increased by 9.05 hours per week
◉ Room turnover improved by 9 percent, from 34 minutes to 31 minutes
◉ Delays were reduced by 7 percent, from 52 percent to 45 percent
◉ On-time first case starts increased by 26 percent, from 20 percent to 46 percent
◉ Add-on cases reduced by 26 percent, from 44 percent to 17 percent

The Children’s Hospital formally released its first scorecard on this project, and it has been an effective control mechanism to monitor results. Maintaining results over time, however, requires putting standard operating procedures in place that will be accepted and applied by the staff.

“We can make adjustments to this process and scorecard as needed,” Dr. Ziegler said, “but beyond the data, it’s really a people issue – it’s about behavior modification. Learning how to structure teams, get people on board, make changes – this has been an institution-wide positive outcome of the project.”

Ensuring multidisciplinary involvement and gaining physician buy-in is essential to making this type of OR initiative work. Weighing the impact on satisfaction also is important. The Children’s Hospital measures customer and employee satisfaction through Press Ganey, and it also developed an internal survey tool it is using to poll the entire perioperative staff. Feedback has been largely positive. One anesthesiologist reported that his area is starting and finishing on time more often. The chief nursing officer indicated that this engagement succeeded where past consulting efforts have failed, in that the team actually implemented change.

By applying the right tools and taking a team-based approach to operational improvement, the project at the Children’s Hospital of Denver helps to illustrate the level of change that is possible within healthcare.

Source: isixsigma.com

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